Journal of System and Computer Engineering
Vol 7 No 3 (2026): JSCE: July 2026

Evaluasi Kinerja SIPETA : Integrasi EUCS dan Teknik Equivalence Partitioning

Litafira Syahadiyanti (Teknik Informatika, Universitas Dr Soetomo, Indonesia)
Pamudi Pamudi (Teknik Informatika, Universitas Dr Soetomo)
Alda Raharja (Teknik Informatika, Universitas Dr Soetomo)
Maulana Zidan Adriansyah (Teknik Informatika, Universitas Dr Soetomo)



Article Info

Publish Date
29 Jul 2026

Abstract

The development of information systems in higher education institutions requires comprehensive performance evaluations to ensure that the systems are capable of supporting learning and administrative processes effectively, efficiently, and in accordance with user needs. This study aims to evaluate the performance of SIPETA in supporting academic processes and to identify factors that affect the quality of the system. The main problems found were suboptimal information quality, data accuracy, and several system functions that affected user trust. The study used an integrative approach with the End User Computing Satisfaction (EUCS) model to measure user satisfaction and the Equivalence Partitioning technique in Black Box testing to assess system functionality. Data was collected through questionnaires administered to 100 users and direct testing of the system's features. The results showed that the system had an effectiveness rate of 86 percent and was rated as good in terms of appearance, ease of use, and timeliness of service. However, the content and accuracy variables were still in the poor category due to several functional failures such as schedule validation, notifications, revision uploads, and guidance history. Overall, SIPETA is suitable for use but requires improvements in data quality and system logic to increase reliability and user satisfaction.

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Journal Info

Abbrev

JSCE

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Programming Languages Algorithms and Theory Computer Architecture and Systems Artificial Intelligence Computer Vision Machine Learning Systems Analysis Data Communications Cloud Computing Object Oriented Systems Analysis and Design Computer and Network Security Data ...